Real-time OPF based on quasi-Newton methods

Optimal power flow is a central problem in the operation of power systems. So far the majority of the literature deals with offline algorithms for traditional applications, but the proliferation of distributed energy resources and smart appliances in power networks motivates real-time and scalable algorithms. We introduce a real-time OPF algorithm based on quasi-Newton methods that can track the optimal operation when the state of the network is changing. Theory and simulations show that the proposed algorithm has guaranteed tracking performance and is computationally efficient.